The approaches described herein as background could be pursued, but are not necessarily approaches that have been previously conceived or pursued. Therefore, unless otherwise indicated herein, the approaches described as background are not prior art to the claims in this application and are not admitted to be prior art by inclusion herein.
Three-dimensional scanning devices generally involve a two stage process of data capture followed by the reconstruction of a 3D image. Data capture involves the collection of raw data which is used to generate the initial geometry of the object being scanned. Typical examples of the data capture process involve contact techniques (e.g. a mechanical probe tracking the surface of an object) and non-contact techniques (such as imaging and range finding techniques). In reconstruction, this data is processed into data suitable for 3D Computer Aided Design (CAD) and/or animation applications.
One such non-contact technique comprises optical technology in which a structured pattern of light is projected onto an object. “A low cost 3D scanner based on structured light”, by C. Rocchini et al in Eurographics 2001, Volume 20, Number 3, describes a technique based on structured light using a non-contact optical scanning technique. A structured pattern of light is projected on to an object and a sensor acquires images of the distorted pattern of light on the surface of the object. Depth information is then reconstructed by triangulation between the sensor, the emitter and the sampled point. Such a technique requires a high degree of accuracy in particular between the monitored positions of the emitter, sensor and a sampled point so that the depth information can be accurately reconstructed. Such techniques require sophisticated devices and calibration each time they are used.
“Calibration-Free Approach to 3D Reconstruction using Light Stripe Projections on a Cube Frame” by Chu et al, Proceedings of the Third International Conference on 3D Digital Imaging and Modelling 2001 describes an example of a system in which a light plane projector projects light onto an object inside a three-dimensional frame. The three-dimensional frame includes a plurality of Light Emitting Diodes (LEDs) which are provided on the corners of the frame. A user waves a laser striper across the object. A sensor in the form of a camera acquires images of the distorted projected pattern of light as reflected from the frame and the surface of the object within the frame. The captured images also include images of the LEDs, which allow the sensor to detect the cube frame.
The camera as used in the implementation described by Chu et al requires no intrinsic calibration. However care has to be taken to fabricate an accurate cube frame and complex image processing is required. In addition the cube frame can cause occlusion of the object. More specifically, shadows can occur at the edges of the cube, which reduces the precision with which edges can be detected to only within a few pixels. Thus the image of the cube is very unlikely to be a cube, and robust statistics must be used to find the image features.
Based on the foregoing, there is a clear need for a scanner device that achieves the required degree of accuracy without requiring complex processing steps or complex reference frames.